International Journal of Industrial Ergonomics 29 (2002) 171–182
Changes in applied force to a touchpad during pointing tasks
Motoyuki Akamatsua, I. Scott MacKenzieb,n
a
Human Environment System Department, National Institute of Bioscience and Human Technology (NIBH), 1-1 Higashi,
Tsukuba 305-8566, Japan
b
Department of Computer Science, York University, 4700 Keele Street, Toronto, Ontario, Canada, M3J 1P3
Received 1 January 2001; accepted 16 September 2001
Abstract
We measured the force applied to a touchpad during pointing tasks for large and small targets. A mouse was also
used as a baseline condition. Our set-up to measure force included a Plexiglas plate mounted on a high-sensitivity threeaxis strain gauge connected to an instrumentation amplifier and a data acquisition computer. The devices were
positioned and operated on top of the plate with the selection button removed and actuated by the opposite hand. An
experiment used 12 participants performing point-select tasks in conformance with ISO 9241-9. At the terminal phase
of the selection tasks, the applied force with the touchpad was lower than that recorded with the mouse. These
differences may be the source of overall performance differences between the two devices. It is suggested that the
detected finger force should be a variable in the touchpad’s transfer function to afford a better blend of coarse and fine
positioning strategies, with the goal being to bring the touchpad more inline with the mouse in overall user
performance.
Relevance to industry
It reports measurements of applied force on the touchpad and mouse pointing devices; demonstrates different
strategies employed by users in the final phase of cursor positioning in target selection tasks; presents opportunities to
improve cursor positioning with touchpads through a transfer function optimized for the applied finger force on the pad
surface. r 2002 Elsevier Science B.V. All rights reserved.
Keywords: Computer pointing devices; Touchpads; Transfer functions; Applied finger force during touchpad interaction
1. Introduction
The popularization of the graphical user interface (GUI) began in 1984 with the Apple
Macintosh. Since then, GUIs have evolved and
E-mail addresses: [email protected] (M. Akamatsu),
[email protected] (I.S. MacKenzie).
n
Corresponding author. Tel.: +1-416-736-2100; fax: +1416-736-5757
matured. A key feature of a GUI is a pointing
device and ‘‘point-and-click’’ interaction. Today,
pointing devices are routinely used by millions of
computer users.
The pointing device most common in desktop
systems is the mouse, although others are also
available, such as trackballs, joysticks, and touchpads. For portable computers, such as laptops or
notebooks, the choice of pointing device is more
limited, however. Due to the constrained operating
0169-8141/02/$ - see front matter r 2002 Elsevier Science B.V. All rights reserved.
PII: S 0 1 6 9 - 8 1 4 1 ( 0 1 ) 0 0 0 6 3 - 4
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M. Akamatsu, I.S. MacKenzie / International Journal of Industrial Ergonomics 29 (2002) 171–182
space, a mouse is generally not practical, and, so,
an alternative pointing device is used.
Early portable computers used either a joystick
or trackball as the pointing device. This changed in
1994 when Apple Computer, Inc. (Cupertino, CA)
introduced the PowerBook 500 series of notebook
computers, the first commercial computer with a
built-in touchpad as a pointing device (MacNeill
and Blickenstorfer, 1996). Since then, numerous
notebook computer manufacturers also adopted
this technology. Today, the trackball is all but
extinct in notebook computers. Joystick usage is
also down, with IBM and Toshiba remaining as
the key players. The touchpad is now the
predominant pointing technology for notebook
computers.
Among the touchpad’s important features are
price and size. It is very inexpensive to manufacture in large quantities, and it is very thin and is
easily installed within the tight confines of a
notebook computer. However, comparative evaluations have established that pointing performance is poor in comparison with a mouse
(Douglas et al., 1999; MacKenzie et al., 2001;
MacKenzie and Oniszczak, 1998).
This research is motivated by the need to
improve the touchpad as an input deviceFto
bring it closer to a mouse in pointing performance.
We investigated user interaction with the touchpad
by measuring the finger force applied to the pad
during pointing tasks. We also measured the force
for the same tasks performed with a mouse. This
paper reports the results of this investigation.
1.1. Control–display relationship
One of the primary functions of a system’s
pointing device is to control the on-screen movement of the cursor. This is known as the control–
display relationship. Where the relationship is a
simple linear one, the term C–D gain is used. For
example, if 3 units of controller movement yield 4
units of cursor movement, C–D gain is 3:4, or 0.75.
As noted by Greenstein and Arnaut (1988), user
performance in target acquisition tasks on touchsensitive tablets is better with gains in the range of
0.8–1.0 than with higher gains or lower gains.
However, gain settings involve a trade-off
between gross positioning time (getting to the
vicinity of a target) and fine positioning time (the
final acquisition), an effect first noted by Jenkins
and Connor (1949). With a high-gain setting, users
can quickly manoeuvre the cursor to the vicinity of
the target, but final acquisition of the target is
exacerbated by the difficulty in precisely controlling the final position of the cursor. Low-gain
settings, on the other hand, facilitate fine positioning of the cursor, but increase the time to advance
the cursor over large distances.
There are other factors affecting the control–
display relationship, such as whether the input
device operates in relative or absolute mode.
Touchpads and mice operate in relative mode,
wherein the relative displacement of the finger on
the touchpad’s surface, or the mouse on the
mousepad’s surface, is used to advance the cursor
relative to its current position. Since the input
surface is small compared with the size of the
output display, a higher gain combined with a
non-linear control–display relationship is often
used. The effect is to reduce the amount of
movement necessary with the input device to
achieve large movement distances in the cursor.
In these cases, the relationship is expressed by a
transfer function instead of a simple ratio. The
transfer function gives the velocity of the cursor as
function of the velocity, or the square of the
velocity, of the finger or mouse (see MacKenzie,
1995). The idea is to optimize both the gross
positioning time and the fine positioning time;
however, the effect on user performance is inconclusive. Jellinek and Card (1990) found no
performance improvement using several higherorder transfer functions with a mouse, and
suggested that the only benefit is the smaller
desktop footprint afforded by the higher-order
relationship. One of the goals of the present
research is to measure and compare the force
profiles for users interacting with touchpads
and mice. We consider this as the first step in
the potential use of force in the transfer function
for touchpads, the goal being to improve the
control–display relationship for touchpads,
making them closer to mouse in overall user
performance.
M. Akamatsu, I.S. MacKenzie / International Journal of Industrial Ergonomics 29 (2002) 171–182
2. Pointing device performance evaluation
The evaluation of a pointing device is tricky at
best, since it involves human subjects. There are
differences between classes of devices (e.g., touchpad vs. trackball) as well as differences within
classes of devices (e.g., finger-controlled trackball
vs. thumb-controlled trackball). Generally, between–class differences are more dramatic, and
hence more easily detected through empirical
evaluations.
2.1. Gross measures
The most common evaluation measures are task
completion time (viz. speed) and accuracy. Task
completion time, usually called movement time
(MT), is simply the elapsed time from the onset of
a trial to the final selection of the target. Accuracy
is usually reported as an error rateFthe percentage of trials where the pointer’s x2y coordinates
upon selection were outside the target region.
These measures are typically analysed over a
variety of task or device conditions. Both movement time and error rate are gross measures
because they are based on a single measurement
at the end of a trial. We will contrast this with fine
measures shortly.
An ISO standard now exists to assist in
evaluating pointing devices. The full standard is
ISO 9241, ‘‘Ergonomic design for office work with
visual display terminals (VDTs)’’. Part 9 is
‘‘Requirements for non-keyboard input device’’
(ISO, 1999). ISO 9241-9 proposes just one
performance measurement: throughput. Throughput, in bits per second, is a composite measure
derived from both the speed and accuracy in
responses. Specifically
IDe
;
MT
ð1Þ
D
þ1 :
We
ð2Þ
Throughput ¼
where
IDe ¼ log2
The term IDe is the effective index of difficulty,
in ‘‘bits’’. It is calculated from D; the distance to
the target, and We ; the effective width of the
173
target. The use of the ‘‘effective’’ width (We ) is
important. We is the width of the distribution of
selection coordinates computed over a sequence of
trials, calculated as
We ¼ 4:133SDx ;
ð3Þ
where SDx is the standard deviation in the
selection coordinates measured along the axis of
approach to the target. This implies that We
reflects the spatial variability (viz. accuracy) in the
sequence of trials. And so, throughput captures
both the speed and accuracy of user performance.
See Douglas and Mithal (1997), Douglas et al.
(1999), and MacKenzie (1992) for detailed discussions.
2.2. Fine measures
Measures such as movement time, error rate,
and throughput are extensively used in pointing
device research (e.g., Batra et al., 1998; Card et al.,
1978; Epps, 1986; Ishiyama and Yano, 2000;
MacKenzie and Buxton, 1992). However, their
expressive power is limited by the simple fact that
they are gross measures. These measures adequately establish that there is a difference, but their
power in eliciting why there is a difference is
limited. Establishing why is more likely borne out
in considering movement behaviour on the way to
the target.
For this, fine measures are needed. Most
commonly, capturing refined aspects of pointing
device behaviour means sampling the x2y coordinates of the pointer path during a trial.
Numerous examples of this exist in the research
literature and they are all motivated by the desire
to examine the fine motor behaviour exhibited
during pointing tasks as influenced by the pointing
device. A few examples are hereby cited. Douglas
and Mithal (1997) sampled the pointer coordinates
during target selection tasks with an isometric
joystick. They found random variations in the
velocity of the pointer, and this they attributed to
finger tremor. Accot and Zhai (1997) sampled the
pointer coordinates during trajectory-based positioning tasks, such as moving the pointer through
a hierarchical menu. They used the sampled data
to build a variation of Fitts’ law for movements
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along a constrained path. Akamatsu and MacKenzie (1995) modified a mouse to include tactile
feedback. They report an evaluation in which five
types of on-target feedback were compared (‘‘normal’’, audio, tactile, visual, and combined). By
capturing x2y sample points and the time when
the pointer entered the target, they were able to
quantitatively compare the effects of the feedback
conditions on the final positioning time, defined as
the time to select the target after first-entry of the
pointer in the target region. They report that
tactile feedback reduces final positioning time.
MacKenzie et al. (2001) present seven new
dependent measures to capture subtle aspects of
pointing device performance. The measures, based
on sampled x2y coordinates, capture performance
features such as pointer direction changes and
target re-entries during target selection tasks.
One measure that has not been captured and
reported on in previous research is the force
applied by the user in interacting with a pointing
device. We feel this is of particular interest for the
touchpad, since users control the on-screen pointer
by moving their finger on the surface of the pad.
Besides x2y motion, z-axis force is required to
maintain tracking. As the velocity of x2y motion
increases and decreases, z-axis force will change;
however, the nature of this change has not been
studied. We suspect that changes in applied force
will reflect a change in the user strategy as
movement proceeds. Furthermore, the effect may
differ between the ballistic phase and the feedbackcontrolled phase of movement (Welford, 1968).
The latter is the final phase of motion wherein the
user hones-in on the target and prepares to select
the target. In the following section, we report on
an experiment to measure the user’s applied force
in interacting with touchpad pointing devices. We
also used a mouse as a baseline condition.
3. Method
3.1. Participants
We recruited 8 volunteer, unpaid participants
for the experiment. All participants were employees at a local laboratory who used computers on a
daily basis. There were 7 males and 1 female. Ages
ranged from 27 to 51 years (mean=37.8, standard
deviation=8.6).
3.2. Apparatus
Hardware: The touchpad and mouse were
operated on a Plexiglas plate (200 cm 165 cm 5 mm) instrumented with a high-sensitivity threeaxis strain gauge. The strain gauge was a model
LSM-1KBS-P by Kyowa Electric Instruments Co
Ltd. (Tokyo, Japan). The strain gauge is connected
to an SAN-EI model 6M92 strain gauge instrumentation amplifier by NEC (Tokyo, Japan),
which in turn is connected to a DAQ Card-700
12-bit analog-to-digital card by National Instruments (Austin, TX). The weight of the device was
subtracted by activating the ‘‘zero balance’’ function of the amplifier prior to testing.
To avoid artefacts in the recorded force, the
click button was separated from the devices and
was operated by the index finger on the left hand.
See Fig. 1.
The touchpad was a Versapad by Interlink
Electronics (Camarillo, CA). It was fixed directly
to the plate by two shafts at diagonally opposing
corners inserted into two holes on the surface of
the plate. See Fig. 2a. The mouse was an
ErgoMouse by Sanwa Supply (Yokahama, Japan).
Both devices connected to the experimental
system’s serial port. When the mouse was used,
the mouse pad was fixed on the plate. See Fig. 2b.
The strain gauge was calibrated to null the effect
of the mass of each device. That is, a force of 0 N
was registered for the apparatus, as seen in Fig. 2.
Participants were allowed to adjust the position
of the device, armrest, and button for maximum
comfort.
When the click button was pressed, a trial
started. The trial was terminated when the
participant pressed the click button again (after
positioning the cursor within the target area). The
signal of the strain gauge and the trace of the onscreen tracking symbol during the task were
recorded at a 33.3 Hz sampling rate.
Two computer systems were used. One system
operated the experimental software and collected
data from the pointing devices. The other system
M. Akamatsu, I.S. MacKenzie / International Journal of Industrial Ergonomics 29 (2002) 171–182
175
Fig. 1. Experimental apparatus. A high-sensitivity three-axis strain gauge supported the devices under test. A separate click button was
operated with the index finger on the left hand.
served as a data acquisition system for the strain
gauge. The system running the experimental software was a Compaq ARMADA 4125T running
Windows 95. Task conditions appeared on a 15 in
CRT display. The data acquisition system was a
Dell HighnoteUltra CT475 running Windows 3.1.
Note that both the experimental software and the
data acquisition software operated in DOS mode.
Software: We used a modified version of
Soukoreff and MacKenzie’s Generalized Fitts’
Law Model Builder software (Soukoreff and
MacKenzie, 1995). The software is DOS-hosted
and runs on any conventional PC platform. The
software was modified to collect pointer trace data
at a controlled sampling rate (33.3 Hz, in this
case). The software uses procedure calls to interact
with the pointing device via the system’s installed
device driver. The experimental conditions presented by the software are described in the next
section.
3.3. Procedure
The task was a standard target acquisition task,
as described in ISO 9241-9 (ISO, 1999). The
participant controlled the position of a tracking
symbolFa crosshairFby manipulating the device
under test in the conventional manner; namely,
moving the mouse, or moving the index finger on
the surface of the touchpad. The target was a
circle. Two different diameters were used: 10 pixels
and 40 pixels.
The distance from the initial pointer position to
the centre of the target was fixed at 160 pixels.
Thus, there were two indices of task difficulty,
based on Eq. (1). For the small target:
160
ID ¼ log2
þ 1 ¼ 4:1 bits
ð4Þ
10
and for the large target
160
þ 1 ¼ 2:3 bits:
ID ¼ log2
40
ð5Þ
Four directions of movement were used: 451,
1351, 2701, 3151.
A timing chart for an example trial is shown in
Fig. 3. At the beginning of a trial a square and a
target circle appear. The participant began a trial
by clicking the button. When this was detected, the
square changed to a crosshair and became the
tracking symbol under control of the pointing
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M. Akamatsu, I.S. MacKenzie / International Journal of Industrial Ergonomics 29 (2002) 171–182
Fig. 2. Devices under test: (a) touchpad (b) mouse. For both devices, the right forearm rested in an arm support (shown) to minimize
the influence of the weight of the forearm on the measured force.
device. The participant moved the tracker by
moving her finger across the pad surface (touchpad condition) or by moving the mouse (mouse
condition). When the tracker was inside the target
the button was pressed again to end the trial. At
the end of a trial, both the crosshair and the target
disappeared. About 2 s later the next condition
appeared.
3.4. Design
Each participant performed two sessions of
trials over two days. We counter-balanced for
device and for target size within device. Two
blocks of trials were administered for each device
and for each target size. A practice block of trials
was administered at the beginning of each session
M. Akamatsu, I.S. MacKenzie / International Journal of Industrial Ergonomics 29 (2002) 171–182
Press the click button
to start a trial
177
Press the button when the
cursor is within the target
Left Hand
Display
Cursor symbol changes from
a square to a cross
Right Hand
The cursor and
target disappear
cursor movement
selection time
Fig. 3. Timing chart for one trial.
Table 1
Sequence of administering experimental conditions
Participant
First session (day #1)
1
2
3
4
5
6
7
8
PM-ML-MS
PM-ML-MS
PM-MS-ML
PM-MS-ML
PT-TL-TS
PT-TL-TS
PT-TS-TL
PT-TS-TL
Second session (day #2)
PT-TL-TS
PT-TS-TL
PT-TS-TL
PT-TL-TS
PM-ML-MS
PM-MS-ML
PM-MS-ML
PM-ML-MS
PT-TL-TS
PT-TL-TS
PT-TS-TL
PT-TS-TL
PM-ML-MS
PM-ML-MS
PM-MS-ML
PM-MS-ML
PM-ML-MS
PM-MS-ML
PM-MS-ML
PM-ML-MS
PT-TL-TS
PT-TS-TL
PT-TS-TL
PT-TL-TS
P=practice, M=mouse, T=touchpad, L=large target, S=small target.
and when switching devices within a session. See
Table 1.
Each letter pair in Table 1 represents a block
of trials (e.g., ‘‘ML’’ is a block of trials for the
mouse with the large target). Each block consisted of eight trials, two for each of the four
angles. Angles were presented randomly within
a block. So, with 8 participants tested in 2 sessions
each containing 6 blocks of 8 trials, the total
number of trials in the experiment was
8 2 6 8=768.
4. Results and discussion
4.1. Gross measures
The grand mean for movement time, excluding
practice blocks, was 1617 ms. Movement with the
mouse (1411 ms) was 23% faster than with the
touchpad (1823 ms). There were also differences by
target size, as expected (see Fig. 4).
The main effect of device on movement time was
significant (F1;7 ¼ 16:6; po0:005), as was the main
M. Akamatsu, I.S. MacKenzie / International Journal of Industrial Ergonomics 29 (2002) 171–182
178
5
2500
Touchpad
Touchpad
Mouse
4
Error Rate (%)
Movement Time (ms)
2000
1500
1000
500
Mouse
3
2
1
0
0
Small
Large
Target Size
Large
Small
Target Size
Fig. 4. Movement time (ms) by device and target size. (Note:
error bars represent 1 standard error.)
Fig. 5. Error rate (%) by device and target size (Note: Error
bars represent 1 standard error.)
effect for target size (F1;7 ¼ 54:8; po0:0001).
However, the device by target size interaction
was not significant (F1;7 ¼ 2:24; p > 0:05).
Error rates were quite low, overall. The grand
mean was 1.56%. There were more errors for the
touchpad (2.34%) than for the mouse (0.78%).
Within devices, there were differences for target
size consistent with those for movement time. The
highest error rate, at 3.91%, was for the touchpad
with the small target (see Fig. 5).
The only statistically significant effect was for
target size (F1;7 ¼ 9:0; po0:05). Note that each
point in Figs. 4 and 5 is the mean score for 128
trials (8 participants 2 blocks 8 trials/block).
The throughput for the mouse was 2.32 bits/s
for the mouse and 1.94 bits/s for the touchpad (see
Eq. (1)). The lower throughput for the touchpad is
consistent with previous studies (e.g., Douglas
et al., 1999; MacKenzie et al., 2001; MacKenzie
and Oniszczak, 1998).
The fact that sample points are seen as clustering together near the end of the trials is indicative
of the deceleration expected as final selection
approaches. The greater distance between sample
points in the middle of the trials is also expected,
as this is the ballistic phase of movement, and it is
during this phase that maximum velocities are
attained.
Maximum velocity: The maximum velocity
attained during each trial was calculated from
the sampled x2y coordinates of the tracker and
from the implicit timestamp associated with each
sample (x2y samples were gathered on 33 ms
intervals). The units were pixels per second. The
results are shown in Fig. 7.
There were no significant main effects or
interactions for device or target size on maximum
velocity. This is an important result. Since the
maximum velocity occurs during the ballistic
phase of movement, and since there was no
significant difference between devices in the maximum velocities, it follows that the touchpad’s
longer selection time was due to the need for
additional or more exacting corrective movements
to fix the cursor to the target.
Applied force: The amplitudes of applied force
to the device were obtained from the sum of the
squares of the forces measured along the three
orthogonal axes. Fig. 8 shows examples of trials
for (a) the mouse and (b) the touchpad. The x-axis
in the figure is the distance (in pixels) to the final
4.2. Fine measures
Our experimental apparatus sampled the position of the tracker and the applied force during
each trail. From these data, a variety of additional
analyses are possible.
Trajectories: By way of example, Fig. 6 shows
the trajectory data as a series of sample points for
a block of eight trials for the touchpad. There are
two trials shown for each angle of movement.
M. Akamatsu, I.S. MacKenzie / International Journal of Industrial Ergonomics 29 (2002) 171–182
179
150
100
50
0
-200
-150
-100
-50
0
50
100
150
200
-50
-100
-150
Fig. 6. Examples of trajectories for eight trials with the touchpad (Note: Units are pixels relative to the centre of the display.)
5300
Maximum Velocity (pixels/s)
5275
5250
Touchpad
Mouse
5225
5200
5175
5150
5125
5100
5075
1
2
Target Size
Fig. 7. Maximum velocity (pixels/s) by device and target size.
(Note: Error bars represent 1 standard error.)
cursor position, while the y-axis is the measured
force (in Newtons).
The figure shows that, in general, the applied
force was reduced on the way to the target.
However, just before the participant stopped the
cursor, there appears to be a small increase in the
force, although there is considerable variability
and the effect is by no means consistent. When
participants used the mouse, the force was
relatively constant until the cursor position was
30 or 20 pixels to the final position. Then, a
gradual increase of the force was observed.
Additionally, we observed that the amplitudes of
the force were higher for the smaller target than
for the larger target.
The mean force by device and target size is
shown in Fig. 9. Although the means were higher
for the mouse than for the touchpad, the main
effect for device was only marginally significant
(F1;7 ¼ 5:10; p ¼ 0:058). Statistical significance was
not attained in the main effect for target size
(F1;7 ¼ 0:34, ns) or in the device by target size
interaction (F1;7 ¼ 2:12; p > 0:05).
Comparison of applied force: From the example
traced in Fig. 8, and from our additional examination of the force profiles, it is evident that changes
in the applied force are complex when the tracker
approaches the target. Therefore, we undertook
further analyses of the force patterns near the
target. The data selected for analysis were for
movements within 10 pixels of the target centre
with the tracker still moving. Since we are looking
for patterns of behaviour within each participant’s
interaction style, the recorded force was standardized by the mean and standard deviations for
each participant, the goal being to null the effect of
individual differences. The lack of significant
difference in the mean applied force (Fig. 9)
justifies this additional adjustment in looking more
closely at the force differences by device. The
results of this final analysis are shown in Fig. 10.
M. Akamatsu, I.S. MacKenzie / International Journal of Industrial Ergonomics 29 (2002) 171–182
180
5
Force (newtons)
4
3
2
1
0
160
140
120
(a)
100
80
60
40
20
0
40
20
0
Distance to Target (pixels)
3
Force (newtons)
2.5
2
1.5
1
0.5
0
160
140
(b)
120
100
80
60
Distance to Target (pixels)
Standardized Applied Force (newtons)
Fig. 8. Examples of recorded applied force for 8 trials: (a) mouse (b) touchpad.
2
Mouse
Mean Force (newtons)
1.8
Touchpad
1.6
1.4
1.2
0.003
Large Target
0.002
Small Target
0.001
0
-0.001
-0.002
-0.003
-0.004
10
9
8
Large
7
6
5
4
3
2
1
0
Distance From Final Position (pixels)
(a)
1
Fig. 9. Mean force (Newtons) by device and target size. (Note:
Error bars represent 1 standard error.)
The number of contributing sample points in
Fig. 10 is 4277 for the mouse (1732 for the large
target, 2545 for the small target) and 5106 for the
touchpad (1988 for the large target, 3118 for the
small target).
Some interesting observations present themselves. As the cursor came close to the target, the
force increased when the participant used the
Standardized Applied Force (newtons)
Small
Target Size
0.008
Large Target
0.006
Small Target
0.004
0.002
0
-0.002
-0.004
10
(b)
9
8
7
6
5
4
3
2
1
0
Distance From Final Position (pixels)
Fig. 10. Comparison of applied force: (a) mouse (b) touchpad.
(Note: Error bars show 1 standard error.)
M. Akamatsu, I.S. MacKenzie / International Journal of Industrial Ergonomics 29 (2002) 171–182
mouse (Fig. 10a). This suggests that users press the
mouse harder when fixing the cursor to the target.
This was also confirmed because the applied force
was higher for the small target than for the large
target. The applied force increases the friction of
mouse movement, potentially helping in the
precise operation of the mouse using hand or
arm movement. This is in part supported implicitly
by the commercial preponderance of mouse pads
with soft, textured surfaces. Since a hand or arm is
less precise than a finger for small and precise
movement (Balakrishnan and MacKenzie, 1997;
Langolf et al., 1976), this is a kind of compensatory behaviour while using a mouse.
On the other hand, when participants used the
touchpad, the force decreased as the cursor
approached the target (Fig. 10b). This suggests
that users reduce their finger force to the touchpad
when they position the cursor in the vicinity of an
intended target. Although this may follow from a
need to reduce finger friction for precise finger
and, hence, tracker movements, the underlying
mechanism for this behaviour is subject to speculation.
One possible explanation for the final decrease
in force for the touchpad is to avoid unstable
tracker movements when the finger presses the
touchpad strongly. When the pad is pressed by the
finger, the friction of the finger tip changes.
Increased friction tends to induce jitter, one
possible explanation being that the skin tissue is
loosely connected to finger bone. This, combined
with the elastic property of the skin may induce
jittery or jerky movement as the skin is alternately
engaged and released from the pad’s surface
during movement. This effect is reduced if the
force is decreased during movement. Since the
metaphor (or analogy) of pointing tasks is ‘‘reaching and pushing a button’’, the natural action for
pointing is to increase the applied force to the
device.
The fact that we observed a decrease in force
during the final positioning of the tracker suggests
that further development in the technology is
warranted to afford more smooth finger and
tracker movements under changes in pressure to
the touchpad. In particular, we feel that force data
have the potential to be used in the transfer
181
function for touchpad devices to improve tracker
motion and to increase the accuracy in the final
positioning of the tracker and to improve the
overall accuracy of selection.
5. Conclusions
We have presented the results of an experiment
that measured the applied force of the finger on a
touchpad during pointing tasks. Our results
indicate that users reduced the applied force of
their finger on the touchpad during the final
selection phase of target acquisition tasks. We
consider this to be an adapted behaviour, however,
it is unnatural and requires effort on the part of
the user. Since the user controls finger force in
positioning tasks, it is suggested that the detected
force should be a variable in the touchpad’s
transfer function to afford a better blend of coarse
and fine positioning strategies.
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